Citations

Abstract Objective The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled “Developing a Clinical Genomic Informatics Research Agenda”. The meeting’s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and Methods Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

AbstractThe eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.

Abstract Objective Clinicians’ ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). Materials and Methods The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. Results There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information enters the EHR through multiple laboratory sources and through clinician notes. For laboratory-based data, the source laboratory was the main determinant of the location of genetic information in the EHR. The highest priority recommendation was to address the need to implement CDS mechanisms and content for decision support for medically actionable genetic information. Conclusion Heterogeneity of genetic information flow and importance of source laboratory, rather than clinical content, as a determinant of information representation are major barriers to using genetic information optimally in patient care. Greater effort to develop interoperable systems to receive and consistently display genetic and/or genomic information and alert clinicians to genomic-dependent improvements to clinical care is recommended.

SummaryBackgroundCommunity‐acquired Clostridium difficile infection (CA‐CDI) is an increasingly appreciated condition. It is being described in populations lacking traditional predisposing factors that have been previously considered at low‐risk for this infection. As most studies of CDI are hospital‐based, outcomes in these patients are not well known.AimTo examine outcomes and their predictors in patients with CA‐CDI.MethodsA sub‐group analysis of a population‐based epidemiological study of CDI in Olmsted county, Minnesota from 1991–2005 was performed. Data regarding outcomes, including severity, treatment response, need for hospitalisation and recurrence were analysed.ResultsOf 157 CA‐CDI cases, the median age was 50 years and 75.3% were female. Among all CA‐CDI cases, 40% required hospitalisation, 20% had severe and 4.4% had severe‐complicated infection, 20% had treatment failure and 28% had recurrent CDI. Patients who required hospitalisation were significantly older (64 years vs. 44 years, P < 0.001), more likely to have severe disease (33.3% vs. 11.7%, P = 0.001), and had higher mean Charlson comorbidity index scores (2.06 vs. 0.84, P = 0.001). They had similar treatment failure and recurrence rates as patients who did not require hospitalisation.ConclusionsCommunity‐acquired Clostridium difficile infection can be associated with complications and poor outcomes, including hospitalisation and severe Clostridium difficile infection. As the incidence of community‐acquired Clostridium difficile infection increases, clinicians should be aware of risk factors (increasing age, comorbid conditions and disease severity) that predict the need for hospitalisation and complications in patients with community‐acquired Clostridium difficile infection.